visualization

Complete guide to visualizing ML experiments with TensorBoard.

Skills
AI research
1

What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

Install the skill (command above).
In Claude Code, describe what you need - the skill turns on by itself when the context fits.
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Install (Claude Code)

mkdir -p .claude/skills/visualization && curl -fsSL https://doutorai.pt/data/lib/skills__visualization.md -o .claude/skills/visualization/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# Comprehensive Visualization Guide

Complete guide to visualizing ML experiments with TensorBoard.

## Table of Contents
- Scalars
- Images
- Histograms & Distributions
- Graphs
- Embeddings
- Text
- PR Curves
- Custom Visualizations

## Scalars

### Basic Scalar Logging

```python
from torch.utils.tensorboard import SummaryWriter

writer = SummaryWriter('runs/scalars_demo')

# Log single metric
for step in range(100):
    loss = compute_loss()
    writer.add_scalar('Loss', loss, step)

writer.close()
```

### Multiple Scalars

```python
# Group related metrics
writer.add_scalars('Loss', {
  

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